app.py

from flask import Flask, render_template, request
import pandas as pd
import pickle
import numpy as np

popularity_df = pickle.load(open('popularity.pkl','rb'))
pt = pickle.load(open('pt.pkl','rb'))
books = pickle.load(open('books.pkl','rb'))
similarity_score = pickle.load(open('similarity_score.pkl','rb'))
book_list = pickle.load(open('book_list.pkl','rb'))


app = Flask(__name__)

@app.route('/')
def index():
    return render_template('index.html',
                           book_name=list(popularity_df['Book-Title'].values),
                           author=list(popularity_df['Book-Author'].values),
                           image=list(popularity_df['Image-URL-M'].values),
                           votes=list(popularity_df['num_ratings'].values),
                           rating=np.round(list(popularity_df['avg_ratings'].values), 2)
                           )

@app.route('/recommend')
def recommend_ui():
    return render_template('recommend.html')

@app.route('/recommend_books', methods=['POST'])
def recommend():

    user_input = request.form.get('user_input')
    indi = np.where(pt.index == user_input)[0][0]
    print('\n',indi)
    print('\n')
    # distances = similarity_score[index]
    similar_items = sorted(list(enumerate(similarity_score[indi])), key=lambda x: x[1], reverse=True)[1:13]

    data = []
    # name = []
    for i in similar_items:
        item = []
        # temp_df1 = book_list[book_list['Book-Title'] == pt.index[i[0]]]
        temp_df = books[books['Book-Title'] == pt.index[i[0]]]
        # name.extend(list(temp_df1.drop_duplicates('Book-Title')['Book-Title'].values))
        item.extend(list(temp_df.drop_duplicates('Book-Title')['Book-Title'].values))
        item.extend(list(temp_df.drop_duplicates('Book-Title')['Book-Author'].values))
        item.extend(list(temp_df.drop_duplicates('Book-Title')['Image-URL-M'].values))

        data.append(item)

    print(data)
    return render_template('recommend.html', data = data)

@app.route('/list')
def listt():
    # name = []
    # for i in book_list:
    #     temp_df1 = book_list[book_list['Book-Title'] == book_list.index[i[0]]]
    #     name.extend(list(temp_df1.drop_duplicates('Book-Title')['Book-Title'].values))

    # return render_template('list.html')
    return render_template('list.html', name=list(books['Book-Title'][1:201].values))
    # return render_template('recommend.html', name = name)


if __name__ == '__main__':
    app.run(debug=True)